STUDY DESIGN: A scoping review design was used.
METHODS: A systematic literature search was conducted using the Medline, CINAHL, AMED, Ageline, PsycINFO, Web of Sciences, Scopus, Thai-Journal Citation Index, MyCite and trial registries databases.
RESULTS: Thirty-seven studies and six study protocols were included, from Thailand, Malaysia, Singapore, Vietnam, Indonesia and the Philippines. One-sixth of the studies involved interventions, while the remainder were observational studies. The observational studies mainly determined the falls risk factors. The intervention studies comprised multifactorial interventions and single interventions such as exercises, educational materials and visual correction. Many of the studies replicated international studies and may not have taken into account features unique to Southeast Asia.
CONCLUSION: Our review has revealed studies evaluating falls and management of falls in the Southeast Asian context. More research is required from all Southeast Asian countries to prepare for the future challenges of managing falls as the population ages.
METHOD: This paper aims to develop a sustainable pedestrian gap crossing index model based on traffic flow density. It focusses on the gaps accepted by pedestrians and their decision for street crossing, where (Log-Gap) logarithm of accepted gaps was used to optimize the result of a model for gap crossing behavior. Through a review of extant literature, 15 influential variables were extracted for further empirical analysis. Subsequently, data from the observation at an uncontrolled mid-block in Jalan Ampang in Kuala Lumpur, Malaysia was gathered and Multiple Linear Regression (MLR) and Binary Logit Model (BLM) techniques were employed to analyze the results.
RESULTS AND CONCLUSIONS: From the results, different pedestrian behavioral characteristics were considered for a minimum gap size model, out of which only a few (four) variables could explain the pedestrian road crossing behavior while the remaining variables have an insignificant effect. Among the different variables, age, rolling gap, vehicle type, and crossing were the most influential variables. The study concludes that pedestrians' decision to cross the street depends on the pedestrian age, rolling gap, vehicle type, and size of traffic gap before crossing.
PRACTICAL APPLICATIONS: The inferences from these models will be useful to increase pedestrian safety and performance evaluation of uncontrolled midblock road crossings in developing countries.